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A gut microbial signature for combination immune checkpoint blockade across cancer types
Ashray Gunjur (Wellcome Sanger Institute), Yan Shao (Wellcome Sanger Institute), Timothy J. Rozday (Wellcome Sanger Institute), Oliver Klein (La Trobe University, Austin Hospital), Andre Mu (European Bioinformatics Institute, Wellcome Sanger Institute), Bastiaan W. Haak (Wellcome Sanger Institute, Amsterdam University Medical Centers), Ben Markman (The Alfred Hospital, Monash Health), Damien Kee (Walter and Eliza Hall Institute of Medical Research, Austin Hospital), Matteo Salvatore Carlino (The University of Sydney, Westmead Hospital), Craig R. Underhill (UNSW Sydney, Albury Wodonga Health), Sophia Frentzas (Monash Health), Michael Michael (The University of Melbourne, Peter MacCallum Cancer Centre), Bo Gao (Westmead Hospital), Jodie Palmer (La Trobe University, Olivia Newton-John Cancer Research Institute), Jonathan Simon Cebon (La Trobe University, Austin Hospital), Andreas Behren (La Trobe University, Olivia Newton-John Cancer Research Institute), David J. Adams (Wellcome Sanger Institute), Trevor D. Lawley (Wellcome Sanger Institute)
Abstract: Immune checkpoint blockade (ICB) targeting programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte protein 4 (CTLA-4) can induce remarkable, yet unpredictable, responses across a variety of cancers. Studies suggest that there is a relationship between a cancer patient's gut microbiota composition and clinical response to ICB; however, defining microbiome-based biomarkers that generalize across cohorts has been challenging. This may relate to previous efforts quantifying microbiota to species (or higher taxonomic rank) abundances, whereas microbial functions are often strain specific. Here, we performed deep shotgun metagenomic sequencing of baseline fecal samples from a unique, richly annotated phase 2 trial cohort of patients with diverse rare cancers treated with combination ICB (n = 106 discovery cohort). We demonstrate that strain-resolved microbial abundances improve machine learning predictions of ICB response and 12-month progression-free survival relative to models built using species-rank quantifications or comprehensive pretreatment clinical factors. Through a meta-analysis of gut metagenomes from a further six comparable studies (n = 364 validation cohort), we found cross-cancer (and cross-country) validity of strain-response signatures, but only when the training and test cohorts used concordant ICB regimens (anti-PD-1 monotherapy or combination anti-PD-1 plus anti-CTLA-4). This suggests that future development of gut microbiome diagnostics or therapeutics should be tailored according to ICB treatment regimen rather than according to cancer type.